Quanming Yao

CEAgent-GSL: Code-level Evolutionary Agent for Interpretable Graph Structure Learning on Omics

This work introduces Evolutionary Rule Abstraction to distill generalized logic from optimization trajectories, overcoming the opacity of traditional evolution, and designs a Counterfactual Validation Module to strictly verify the causal reliability of abstracted rules.